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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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A data-efficient and trustworthy machine learning approach is developed for automated inverse analysis of small angle scattering data.
A mutation of the axial methionine to leucine unexpectedly lowered the reduction potential of type 1 copper in small laccase, attributable to the presence of water. Two additional mutations removed the water, increasing the potential and activity.
Single-stranded DNA molecules modified with cholesterol functional groups are physically tethered to silica nanoparticles (diameter 25 nm) that are encapsulated in a lipid bilayer. Such tethering increases the azimuthal mobility of the DNA molecules across the nanoparticle surface and enables nonspecific bonding, eliminating the need for specialized surface chemistries (such as silane or thiol ligands). To induce assembly, double-stranded DNA ‘bridge’ molecules are then added with complementary nucleotides to the DNA ‘anchor’ molecules that are physically tethered to the lipids on the surface of the particles. Assembly is observed to occur at room temperature and without the need for temperature annealing. Using automated liquid handling tools, assemblies are created in high throughput and rapidly characterized using SAXS. It is determined that the relative concentration of DNA-to-silica and the ionic strength of the solution are important parameters that affect the resulting assembly. Analysis of SAXS data is performed using coarse-grained particle dynamics simulations. The results support the spontaneous formation of semi-crystalline particle assemblies by particle condensation, where the interparticle distance is tuned by the sequence of the DNA ‘bridge’ used to link the particles. Crystallinity analysis performed on the resulting simulations, optimized to match SAXS observations, suggest that particle clusters display increased crystallinity in the center of the clusters, but their maximum size remains relatively small (sub-micron) before settling occurs, which limits the extent of crystallization.
Macroscopic phase equilibria between solutions define the functionality of many biological and industrial processes, yet they are challenging to predict due to the inherent complexity of liquids containing large molecules. This work introduces an approach for the purely predictive calculation of such phase equilibria in temperature-composition space from molecular dynamics (MD) simulations at one temperature in the single-phase region. We use an approach developed previously to obtain the entropic and enthalpic contributions to the free energy of mixing from the atomic-scale information given by MD simulations via Kirkwood–Buff theory. This allows us to accurately estimate the free energy of mixing as a function of temperature, and thus obtain liquid–liquid phase equilibria, including liquid–liquid critical points, associated binodal and spinodal lines, and composition fluctuations across a region of temperature and composition. Results for binary malonamide–alkane systems are validated by comparison to a direct experimental probe of the fluctuations: the small angle X-ray scattering intensity near zero wavenumber. The MDKB → Phase method demonstrated here provides a significant improvement in predicting liquid–liquid equilibria and free energy as a function of temperature for our systems of interest compared to conventional thermodynamic models. The accurate performance of this purely predictive approach lies in its preservation of atomistic details when determining thermodynamic properties. Furthermore, its inherent extensibility to multi-component systems will likely make the MDKB → Phase approach a valuable general tool for connecting molecular interactions to macroscopic phase equilibria and for the computational screening of materials for targeted thermodynamic behavior.
The carbohydrate response element binding protein (ChREBP) is a glucose-responsive transcription factor that plays a critical role in glucose-mediated induction of genes involved in hepatic glycolysis and lipogenesis. In response to fluctuating blood glucose levels ChREBP activity is regulated mainly by nucleocytoplasmic shuttling of ChREBP. Under high glucose ChREBP binds to importin α and importin β and translocates into the nucleus to initiate transcription. We have previously shown that the nuclear localization signal site (NLS) for ChREBP is bipartite with the NLS extending from Arg158 to Lys190. Here, we report the 2.5 Å crystal structure of the ChREBP-NLS peptide bound to importin α. The structure revealed that the NLS binding is monopartite, with the amino acid residues K171RRI174 from the ChREBP-NLS interacting with ARM2–ARM5 on importin α. We discovered that importin α also binds to the primary binding site of the 14-3-3 proteins with high affinity, which suggests that both importin α and 14-3-3 are each competing with the other for this broad-binding region (residues 117–196) on ChREBP. We screened a small compound library and identified two novel compounds that inhibit the ChREBP-NLS/importin α interaction, nuclear localization, and transcription activities of ChREBP. These candidate molecules support developing inhibitors of ChREBP that may be useful in treatment of obesity and the associated diseases.
Results on collisions of O-16 nuclei performed at the Relativistic Heavy Ion Collider (RHIC) have been presented for the first time at Quark Matter 2023 by the STAR collaboration. O-16+O-16 collisions are also expected to take place in the near future at the Large Hadron Collider (LHC) at much higher beam energies. We explore the potential of beam-energy-dependent studies for this system to probe small-x dynamics and QCD evolution. We perform 3+1D IP-Glasma simulations to predict the rapidity dependence of the initial geometry of light-ion collisions, focusing on O-16+O-16 and Ne-20+Ne-20 collisions at root s(NN) = 70 GeV and 7 TeV. The choice of Ne-20 is motivated by its strongly elongated geometry, which may respond differently to the effect of the high-energy evolution compared to the more spherical O-16. We find that smearing induced by soft gluon production at high energy causes mild variations in the initial-state eccentricities as a function of the collision energy. These effects could be resolved in future experiments and deserve further investigation.
Within a (3+1)D viscous hydrodynamic model we compute anisotropic flow in small system collisions as performed at the Relativistic Heavy Ion Collider and measured by the STAR and PHENIX Collaborations. We emphasize the importance of the rapidity dependence of the geometry for interpreting the differences encountered in measurements by the two collaborations.
In this work an initial electron cyclotron heating/current drive (EC H&CD) scoping study is presented for the SMall Aspect Ratio Tokamak (SMART), constructed and operated by the Plasma Science and Fusion Technology (PSFT) Laboratory of the University of Seville. We consider two planned phases of operation with different magnitude of magnetic field (B 0.4, and 1 T). This EC H&CD scoping study is carried out by using the ray tracing code TRAVIS, which allows to quickly perform a series of scans on the main SMART plasma scenarios. A scan in the poloidal and toroidal launching angles is performed for the B 0.4 T plasma scenario assuming three launching locations (mid-plane, off-mid-plane, and top-launcher) and the extraordinary (X-) mode polarization. The absorption occurs at the second harmonic and, overall, the highest power absorption is obtained launching the EC beam from the top of the machine. A numerical analysis of the fundamental X-mode EC H&CD start-up regime for the B 1.0 T plasma scenario with two different wave frequencies (28 and 35 GHz) is presented showing a very high current drive efficiency.
Here, this study examines the application of the recently developed next-generation intensity-duration-frequency (NG-IDF) curves in hydrological design, focusing on a small snow-dominated basin in Washington state. Four methods are used to assess the NG-IDF performance: (1) basin outlet flood frequency analysis, (2) use of standard precipitation-based intensity-duration-frequency (PREC-IDF) curves following surface water design manuals typically used in the basin, (3) utilization of locally constructed PREC-IDF curves, and (4) use of locally constructed NG-IDF curves. The standard PREC-IDF design method assumes precipitation as rainfall and neglecting snowmelt or rain-on-snow (ROS) events that can lead to significant flood underestimations in the test basin. In contrast, the NG-IDF method incorporates snow processes and shows promising improvements in accurately estimating design floods. The validation analysis demonstrates the superiority of NG-IDF over standard and local PREC-IDF in this test basin. The study highlights the necessity for adjustments in current design manuals to ensure sufficient flood protection, particularly in light of the planned substantial investments in US infrastructure.
Here, this paper presents a closure to “Observation-Based Evaluation of Flood Estimation Techniques for a Small Snow-Dominated Basin in the Washington Cascade Mountains” by Hongxiang Yan, Zhuoran Duan, Mark S. Wigmosta, Ning Sun, Ethan D. Gutmann, Bert Kruyt, and Jeffrey R. Arnold. https://doi.org/10.1061/JHYEFF .HEENG-6147.
We report Fermi surface characteristics of Mo 8 Ga 41 , a two-gap superconductor with critical temperature T c ~10 K, obtained from quantum oscillation measurements. Four major frequencies have been observed with relatively small quastiparticle masses. Angular dependence of major frequencies indicates three-dimensional Fermi surface sheets. This argues for a relatively isotropic superconducting state and, given its relatively high T c , shows that a search for new materials in this class could be of interest for superconducting wire applications.
Self-assembly of amphiphilic polymers in water is of fundamental and practical importance. Significant amounts of free unimers and associated micellar aggregates often coexist over a wide range of phase regions. The thermodynamic and kinetic properties of the microphase separation are closely related to the relative population density of unimers and micelles. Although the scattering technique has been employed to identify the structure of micellar aggregates as well as their time-evolution, the determination of the population ratio of micelles to unimers remains a challenging problem due to their difference in scattering power. In this work, using small-angle neutron scattering (SANS), we present a comprehensive structural study of amphiphilic n-dodecyl-PNIPAm polymers, which shows a bimodal size distribution in water. By adjusting the deuterium/hydrogen ratio of water, the intra-micellar polymer and water distributions are obtained from the SANS spectra. The micellar size and number density are further determined, and the population densities of micelles and unimers are calculated to quantitatively address the degree of micellization at different temperatures. Our method can be used to provide an in-depth insight into the solution properties of microphase separation, which are present in many amphiphilic systems.
Here, we report quantum oscillation measurements of LaAlGe, a Lorentz-violating type-II Weyl semimetal with tilted Weyl cones. Very small quasiparticle masses and very high Fermi velocities were detected at the Fermi surface. Whereas three main frequencies have been observed, the angular dependence of two Fermi surface sheets indicates possible two-dimensional (2D) character despite the absence of the 2D structural features such as van der Waals bonds. Such conducting states may offer a good platform for low-dimensional polarized spin current in magnetic RAlGe (R = Ce, Pr) materials.
The strength distribution of polysilicon bend specimens, approximately 10 μm in size, is measured using a high-throughput microelectromechanical system fabrication and testing method. The distribution is predicted from reference tests on tensile specimens and finite element analysis of the bend specimen geometry incorporated into a stochastic extreme-value strength framework. Agreement between experiment and prediction suggests that the ultra-small specimens may be at the limit of extreme-value scaling and contain only one strength-controlling flaw/specimen.
Analytical self-similar solutions to two-, three-, and four-equation Reynolds-averaged mechanical–scalar turbulence models describing incompressible turbulent Rayleigh–Taylor, Richtmyer–Meshkov, and Kelvin–Helmholtz instability-induced mixing in planar geometry are derived in the small Atwood number (Boussinesq) limit. The models are based on the turbulent kinetic energy K and its dissipation rate ε, together with the scalar (heavy-fluid mass fraction) variance S and its dissipation rate Χ modeled either differentially or algebraically. The models allow for a simultaneous description of mechanical and scalar mixing, i.e., mixing layer growth and molecular mixing, respectively. Mixing layer growth parameters and other physical observables relevant to each instability are obtained explicitly as functions of the model coefficients. The turbulent fields are also expressed in terms of the model coefficients, with their temporal power-law scalings obtained by requiring that the self-similar equations are explicitly time-independent. The model calibration methodology is described and discussed. Expressions for a subset of the various physical observables are used to calibrate each of the two-, three-, and four-equation models, such that the self-similar solutions are consistent with experimental and numerical simulation data corresponding to these values of the observables and to specific canonical Rayleigh–Taylor, Richtmyer–Meshkov, and Kelvin–Helmholtz turbulent flows. A calibrated four-equation model is then used to reconstruct the mean and turbulent fields, and late-time turbulent equation budgets for each instability-induced flow across the mixing layer. The reference solutions derived here can provide systematic calibrations and better understanding of mechanical–scalar turbulence models and their predictions for instability-induced turbulent mixing in the very large Reynolds number limit.
Cryogenic deuterium–tritium ice target implosions on OMEGA with new small-spot (SG5-650) distributed phase plates (DPPs) achieved an (11 ± 4)% increase in energy coupling compared to implosions with larger-spot SG5-850 DPPs by decreasing the ratio of the laser spot diameter to the target diameter from 0.93 to 0.75. The SG5-650 DPPs provide a focus spot size of 674 μm, which is defined as the diameter that encircles 95% of the measured beam energy compared to 834 μm for the SG5-850, which are the standard DPPs in cryogenic target implosions on OMEGA. The hydrodynamic efficiency, defined as the ratio of the kinetic energy in the imploding shell to the laser energy, increased from 4.5% to 5.0% based on radiation-hydrodynamic calculations benchmarked to shell trajectory and bang-time measurements. Furthermore, the higher coupling came with a trade-off of an increased hot-electron production as well as increased hydrodynamic instabilities seeded by a larger mode-10 amplitude from the beam port geometry, both of which may have reduced the fusion neutron production and areal density.
Achieving highly efficient energy conversion with transition metal oxides necessitates overcoming conductivity limitations due to the formation of small polarons. Detailed understanding of the interplay among intrinsic defects, dopants, and electron polarons can help devise strategies for achieving higher carrier concentrations, therefore improving carrier conductivity. This work employs first-principles calculations to reliably predict electron polaron concentrations in a prominent polaronic oxide, hematite (Fe 2 O 3 ), by resolving interactions between charged defects and electron polarons and keeping charge neutrality condition among all charged species. This work addresses that both V O and Fe i can be primary donors in undoped hematite depending on the synthesis conditions, such as synthesis temperature and oxygen partial pressure, despite the fact that V O owns an extremely high ionization energy compared to k B T. Furthermore, from calculations of a plethora of n-type dopants (group IV and V elements), we find that Ti, Ge, Sb, and Nb are able to raise electron polaron concentrations in hematite significantly without considering dopant clustering. However, the magnitude of electron polaron concentration increase would be smaller if the dopant has a high tendency of clustering, such as Ti. Here we reveal the critical role of synthesis conditions on tuning electron polaron concentrations of both undoped and doped hematite. Our theoretical analysis provides important insights and general design principles for engineering more conductive polaronic oxides.
We outline a machine learning strategy for quantitively determining the conformation of AB-type diblock copolymers with excluded volume effects using small angle scattering. Complemented by computer simulations, a correlation matrix connecting conformations of different copolymers according to their scattering features is established on the mathematical framework of a Gaussian process, a multivariate extension of the familiar univariate Gaussian distribution. We show that the relevant conformational characteristics of copolymers can be probabilistically inferred from their coherent scattering cross sections without any restriction imposed by model assumptions. This work not only facilitates the quantitative structural analysis of copolymer solutions but also provides the reliable benchmarking for the related theoretical development of scattering functions.